Configuration Optimization Methods In Product Family Design Process Of Banknote Sorting Machine

The financial machinery enterprises are facing with the problem providing proper product design for different kinds of customers especially under the increasingly fierce competition in the international market. The currency sorting machine is important and necessary cash processing equipment in the financial industry. It has the characteristics of complex structure, intelligence and changing demand.In order to meet the personalized products demand as quickly as possible and at the lowest cost, the dissertation carried out an in-depth research on some key problems of the product family design of banknote sorting machine in the process of design for mass customization. The dissertation presents new methods combining banknote sorting machine structure, design features and development processes. The research findings are applied successfully in practice. The main research contents in this dissertation are described as follows:(1) The development process of banknote sorting machine is analyzed in detail taking into account product structure and features based on the product family design-oriented theory and key technology. The multi-views modeling method and the task structures in the product development process are proposed. The mapping mechanism from the task structure of the product development process to the workflow net is set up. The design verification results of banknote sorting machine development process based on WF-NET show that the proposed method can effectively realize the task distribution and performance estimation for analysis the product development cycle accurately and quantitatively.(2) The research on the method for determining product platform design modules in the process of modularized product family design is carried out based on fuzzy C-means (FCM) clustering algorithm optimized by the improved shuffled frog leaping algorithm (SFLA). The component coefficient matrix based on the datum collected is set up. The number of fuzzy clustering and cluster centers are optimized by sizable-individual SFLA to obtain the optimized fuzzy partition of the components. The simulation results of the product family design of the banknote sorting machine show that the proposed method supplies the theory basis of the quantity mathematic analysis and fast configuration for the product family design. (3) A method of product family configuration performance prediction is proposed in the process of product design. The new variant product performances are predicted through the data mining on the historical datum of banknote sorting machine product family under the framework of configuration comprehensive performance prediction method based on SVM. An improved shuffled frog leaping algorithm (SFLA) is adopted to optimize the kernel function parameters and error penalty factors of the SVM models, where the simulated annealing algorithm is used to increase local searching ability and convergence velocity.Finally, the proposed method is verified on a newly developed module-based banknote sorting machine product family to assess the effectiveness of predicting the configuration performances of the module-based product family design accurately and quickly.